Pandas Profiling Report

Dataset statistics

Number of variables	37
Number of observations	700
Missing cells	700
Missing cells (%)	2.7%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	202.5 KiB
Average record size in memory	296.2 B

Variable types

Categorical	25
Numeric	11
Unsupported	1

Warnings

`Customer_ID` has a high cardinality: 700 distinct values	High cardinality
`policy_bind_date` has a high cardinality: 671 distinct values	High cardinality
`incident_location` has a high cardinality: 700 distinct values	High cardinality
`incident_date` has a high cardinality: 60 distinct values	High cardinality
`months_as_customer` is highly correlated with `age`	High correlation
`age` is highly correlated with `months_as_customer`	High correlation
`auto_model` is highly correlated with `auto_make`	High correlation
`auto_make` is highly correlated with `auto_model`	High correlation
`_c39` has 700 (100.0%) missing values	Missing
`Customer_ID` is uniformly distributed	Uniform
`policy_bind_date` is uniformly distributed	Uniform
`incident_location` is uniformly distributed	Uniform
`Customer_ID` has unique values	Unique
`policy_number` has unique values	Unique
`incident_location` has unique values	Unique
`_c39` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`capital-gains` has 350 (50.0%) zeros	Zeros
`capital-loss` has 326 (46.6%) zeros	Zeros
`incident_hour_of_the_day` has 40 (5.7%) zeros	Zeros
`umbrella_limit` has 561 (80.1%) zeros	Zeros

Reproduction

Analysis started	2021-04-19 12:03:44.240394
Analysis finished	2021-04-19 12:04:16.246564
Duration	32.01 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

Customer_ID
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	700
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Customer_352	1
Customer_401	1
Customer_898	1
Customer_806	1
Customer_951	1
Other values (695)	695

Length

Max length	12
Median length	12
Mean length	11.9
Min length	10

Characters and Unicode

Total characters	8330
Distinct characters	19
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	700 ?
Unique (%)	100.0%

Sample

1st row	Customer_541
2nd row	Customer_440
3rd row	Customer_482
4th row	Customer_422
5th row	Customer_778

Value	Count	Frequency (%)
Customer_352	1	0.1%
Customer_401	1	0.1%
Customer_898	1	0.1%
Customer_806	1	0.1%
Customer_951	1	0.1%
Customer_927	1	0.1%
Customer_279	1	0.1%
Customer_420	1	0.1%
Customer_58	1	0.1%
Customer_614	1	0.1%
Other values (690)	690	98.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
customer_177	1	0.1%
customer_46	1	0.1%
customer_735	1	0.1%
customer_222	1	0.1%
customer_268	1	0.1%
customer_154	1	0.1%
customer_257	1	0.1%
customer_976	1	0.1%
customer_140	1	0.1%
customer_605	1	0.1%
Other values (690)	690	98.6%

Most occurring characters

Value	Count	Frequency (%)
C	700	8.4%
u	700	8.4%
s	700	8.4%
t	700	8.4%
o	700	8.4%
m	700	8.4%
e	700	8.4%
r	700	8.4%
_	700	8.4%
1	219	2.6%
Other values (9)	1811	21.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4900	58.8%
Decimal Number	2030	24.4%
Uppercase Letter	700	8.4%
Connector Punctuation	700	8.4%

Most frequent character per category

Value	Count	Frequency (%)
1	219	10.8%
7	219	10.8%
4	216	10.6%
8	214	10.5%
5	211	10.4%
3	210	10.3%
2	208	10.2%
6	208	10.2%
9	186	9.2%
0	139	6.8%

Value	Count	Frequency (%)
u	700	14.3%
s	700	14.3%
t	700	14.3%
o	700	14.3%
m	700	14.3%
e	700	14.3%
r	700	14.3%

Value	Count	Frequency (%)
C	700	100.0%

Value	Count	Frequency (%)
_	700	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5600	67.2%
Common	2730	32.8%

Most frequent character per script

Value	Count	Frequency (%)
_	700	25.6%
1	219	8.0%
7	219	8.0%
4	216	7.9%
8	214	7.8%
5	211	7.7%
3	210	7.7%
2	208	7.6%
6	208	7.6%
9	186	6.8%

Value	Count	Frequency (%)
C	700	12.5%
u	700	12.5%
s	700	12.5%
t	700	12.5%
o	700	12.5%
m	700	12.5%
e	700	12.5%
r	700	12.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8330	100.0%

Most frequent character per block

Value	Count	Frequency (%)
C	700	8.4%
u	700	8.4%
s	700	8.4%
t	700	8.4%
o	700	8.4%
m	700	8.4%
e	700	8.4%
r	700	8.4%
_	700	8.4%
1	219	2.6%
Other values (9)	1811	21.7%

months_as_customer
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	346
Distinct (%)	49.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	209.5285714
Minimum	0
Maximum	479
Zeros	1
Zeros (%)	0.1%
Memory size	5.6 KiB

Quantile statistics

Minimum	0
5-th percentile	32
Q1	123
median	209
Q3	283
95-th percentile	434.05
Maximum	479
Range	479
Interquartile range (IQR)	160

Descriptive statistics

Standard deviation	114.746174
Coefficient of variation (CV)	0.5476397477
Kurtosis	-0.5107224877
Mean	209.5285714
Median Absolute Deviation (MAD)	80.5
Skewness	0.3307605275
Sum	146670
Variance	13166.68445
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
230	6	0.9%
295	6	0.9%
222	6	0.9%
245	6	0.9%
290	6	0.9%
285	5	0.7%
163	5	0.7%
143	5	0.7%
128	5	0.7%
126	5	0.7%
Other values (336)	645	92.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	0.1%
1	1	0.1%
2	2	0.3%
3	1	0.1%
4	2	0.3%

Value	Count	Frequency (%)
479	1	0.1%
478	1	0.1%
476	1	0.1%
475	1	0.1%
473	1	0.1%

age
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	46
Distinct (%)	6.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	39.41714286
Minimum	19
Maximum	64
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	19
5-th percentile	26
Q1	32
median	39
Q3	45
95-th percentile	57
Maximum	64
Range	45
Interquartile range (IQR)	13

Descriptive statistics

Standard deviation	9.170472168
Coefficient of variation (CV)	0.2326518744
Kurtosis	-0.2994174588
Mean	39.41714286
Median Absolute Deviation (MAD)	6
Skewness	0.4700257301
Sum	27592
Variance	84.09755978
Monotocity	Not monotonic

Histogram with fixed size bins (bins=46)

Value	Count	Frequency (%)
39	38	5.4%
43	36	5.1%
34	32	4.6%
32	31	4.4%
38	30	4.3%
41	29	4.1%
37	27	3.9%
31	27	3.9%
40	26	3.7%
33	26	3.7%
Other values (36)	398	56.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
19	1	0.1%
20	1	0.1%
21	3	0.4%
22	1	0.1%
23	3	0.4%

Value	Count	Frequency (%)
64	1	0.1%
63	1	0.1%
62	3	0.4%
61	9	1.3%
60	8	1.1%

insured_sex
Categorical

Distinct	2
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

FEMALE	367
MALE	333

Length

Max length	6
Median length	6
Mean length	5.048571429
Min length	4

Characters and Unicode

Total characters	3534
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	FEMALE
2nd row	MALE
3rd row	MALE
4th row	MALE
5th row	MALE

Value	Count	Frequency (%)
FEMALE	367	52.4%
MALE	333	47.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
female	367	52.4%
male	333	47.6%

Most occurring characters

Value	Count	Frequency (%)
E	1067	30.2%
M	700	19.8%
A	700	19.8%
L	700	19.8%
F	367	10.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	3534	100.0%

Most frequent character per category

Value	Count	Frequency (%)
E	1067	30.2%
M	700	19.8%
A	700	19.8%
L	700	19.8%
F	367	10.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3534	100.0%

Most frequent character per script

Value	Count	Frequency (%)
E	1067	30.2%
M	700	19.8%
A	700	19.8%
L	700	19.8%
F	367	10.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3534	100.0%

Most frequent character per block

Value	Count	Frequency (%)
E	1067	30.2%
M	700	19.8%
A	700	19.8%
L	700	19.8%
F	367	10.4%

insured_education_level
Categorical

Distinct	7
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

JD	117
High School	115
MD	108
Associate	104
College	90
Other values (2)	166

Length

Max length	11
Median length	7
Mean length	5.912857143
Min length	2

Characters and Unicode

Total characters	4139
Distinct characters	20
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	JD
2nd row	Masters
3rd row	JD
4th row	High School
5th row	PhD

Value	Count	Frequency (%)
JD	117	16.7%
High School	115	16.4%
MD	108	15.4%
Associate	104	14.9%
College	90	12.9%
Masters	90	12.9%
PhD	76	10.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
jd	117	14.4%
high	115	14.1%
school	115	14.1%
md	108	13.3%
associate	104	12.8%
college	90	11.0%
masters	90	11.0%
phd	76	9.3%

Most occurring characters

Value	Count	Frequency (%)
o	424	10.2%
s	388	9.4%
e	374	9.0%
h	306	7.4%
D	301	7.3%
l	295	7.1%
i	219	5.3%
c	219	5.3%
g	205	5.0%
M	198	4.8%
Other values (10)	1210	29.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2908	70.3%
Uppercase Letter	1116	27.0%
Space Separator	115	2.8%

Most frequent character per category

Value	Count	Frequency (%)
o	424	14.6%
s	388	13.3%
e	374	12.9%
h	306	10.5%
l	295	10.1%
i	219	7.5%
c	219	7.5%
g	205	7.0%
a	194	6.7%
t	194	6.7%

Value	Count	Frequency (%)
D	301	27.0%
M	198	17.7%
J	117	10.5%
H	115	10.3%
S	115	10.3%
A	104	9.3%
C	90	8.1%
P	76	6.8%

Value	Count	Frequency (%)
	115	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4024	97.2%
Common	115	2.8%

Most frequent character per script

Value	Count	Frequency (%)
o	424	10.5%
s	388	9.6%
e	374	9.3%
h	306	7.6%
D	301	7.5%
l	295	7.3%
i	219	5.4%
c	219	5.4%
g	205	5.1%
M	198	4.9%
Other values (9)	1095	27.2%

Value	Count	Frequency (%)
	115	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4139	100.0%

Most frequent character per block

Value	Count	Frequency (%)
o	424	10.2%
s	388	9.4%
e	374	9.0%
h	306	7.4%
D	301	7.3%
l	295	7.1%
i	219	5.3%
c	219	5.3%
g	205	5.0%
M	198	4.8%
Other values (10)	1210	29.2%

insured_occupation
Categorical

Distinct	14
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

machine-op-inspct	72
exec-managerial	57
tech-support	56
prof-specialty	55
other-service	52
Other values (9)	408

Length

Max length	17
Median length	14
Mean length	13.55714286
Min length	5

Characters and Unicode

Total characters	9490
Distinct characters	21
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	farming-fishing
2nd row	protective-serv
3rd row	handlers-cleaners
4th row	handlers-cleaners
5th row	priv-house-serv

Value	Count	Frequency (%)
machine-op-inspct	72	10.3%
exec-managerial	57	8.1%
tech-support	56	8.0%
prof-specialty	55	7.9%
other-service	52	7.4%
craft-repair	50	7.1%
sales	50	7.1%
armed-forces	49	7.0%
adm-clerical	48	6.9%
protective-serv	48	6.9%
Other values (4)	163	23.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
machine-op-inspct	72	10.3%
exec-managerial	57	8.1%
tech-support	56	8.0%
prof-specialty	55	7.9%
other-service	52	7.4%
craft-repair	50	7.1%
sales	50	7.1%
armed-forces	49	7.0%
adm-clerical	48	6.9%
protective-serv	48	6.9%
Other values (4)	163	23.3%

Most occurring characters

Value	Count	Frequency (%)
e	1090	11.5%
r	951	10.0%
-	766	8.1%
a	746	7.9%
s	673	7.1%
i	661	7.0%
c	641	6.8%
p	554	5.8%
t	529	5.6%
o	468	4.9%
Other values (11)	2411	25.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	8724	91.9%
Dash Punctuation	766	8.1%

Most frequent character per category

Value	Count	Frequency (%)
e	1090	12.5%
r	951	10.9%
a	746	8.6%
s	673	7.7%
i	661	7.6%
c	641	7.3%
p	554	6.4%
t	529	6.1%
o	468	5.4%
n	439	5.0%
Other values (10)	1972	22.6%

Value	Count	Frequency (%)
-	766	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	8724	91.9%
Common	766	8.1%

Most frequent character per script

Value	Count	Frequency (%)
e	1090	12.5%
r	951	10.9%
a	746	8.6%
s	673	7.7%
i	661	7.6%
c	641	7.3%
p	554	6.4%
t	529	6.1%
o	468	5.4%
n	439	5.0%
Other values (10)	1972	22.6%

Value	Count	Frequency (%)
-	766	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	9490	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	1090	11.5%
r	951	10.0%
-	766	8.1%
a	746	7.9%
s	673	7.1%
i	661	7.0%
c	641	6.8%
p	554	5.8%
t	529	5.6%
o	468	4.9%
Other values (11)	2411	25.4%

insured_hobbies
Categorical

Distinct	20
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

camping	45
reading	44
exercise	43
hiking	41
yachting	40
Other values (15)	487

Length

Max length	14
Median length	8
Mean length	8.107142857
Min length	4

Characters and Unicode

Total characters	5675
Distinct characters	24
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	paintball
2nd row	yachting
3rd row	golf
4th row	hiking
5th row	exercise

Value	Count	Frequency (%)
camping	45	6.4%
reading	44	6.3%
exercise	43	6.1%
hiking	41	5.9%
yachting	40	5.7%
paintball	38	5.4%
golf	38	5.4%
bungie-jumping	37	5.3%
kayaking	37	5.3%
base-jumping	37	5.3%
Other values (10)	300	42.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
camping	45	6.4%
reading	44	6.3%
exercise	43	6.1%
hiking	41	5.9%
yachting	40	5.7%
paintball	38	5.4%
golf	38	5.4%
bungie-jumping	37	5.3%
kayaking	37	5.3%
base-jumping	37	5.3%
Other values (10)	300	42.9%

Most occurring characters

Value	Count	Frequency (%)
i	658	11.6%
g	513	9.0%
a	488	8.6%
e	486	8.6%
n	478	8.4%
s	381	6.7%
o	221	3.9%
m	219	3.9%
c	217	3.8%
p	213	3.8%
Other values (14)	1801	31.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5509	97.1%
Dash Punctuation	166	2.9%

Most frequent character per category

Value	Count	Frequency (%)
i	658	11.9%
g	513	9.3%
a	488	8.9%
e	486	8.8%
n	478	8.7%
s	381	6.9%
o	221	4.0%
m	219	4.0%
c	217	3.9%
p	213	3.9%
Other values (13)	1635	29.7%

Value	Count	Frequency (%)
-	166	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5509	97.1%
Common	166	2.9%

Most frequent character per script

Value	Count	Frequency (%)
i	658	11.9%
g	513	9.3%
a	488	8.9%
e	486	8.8%
n	478	8.7%
s	381	6.9%
o	221	4.0%
m	219	4.0%
c	217	3.9%
p	213	3.9%
Other values (13)	1635	29.7%

Value	Count	Frequency (%)
-	166	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5675	100.0%

Most frequent character per block

Value	Count	Frequency (%)
i	658	11.6%
g	513	9.0%
a	488	8.6%
e	486	8.6%
n	478	8.4%
s	381	6.7%
o	221	3.9%
m	219	3.9%
c	217	3.8%
p	213	3.8%
Other values (14)	1801	31.7%

insured_relationship
Categorical

Distinct	6
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

own-child	127
other-relative	121
not-in-family	119
husband	116
wife	116

Length

Max length	14
Median length	9
Mean length	9.384285714
Min length	4

Characters and Unicode

Total characters	6569
Distinct characters	20
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	other-relative
2nd row	not-in-family
3rd row	not-in-family
4th row	husband
5th row	not-in-family

Value	Count	Frequency (%)
own-child	127	18.1%
other-relative	121	17.3%
not-in-family	119	17.0%
husband	116	16.6%
wife	116	16.6%
unmarried	101	14.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
own-child	127	18.1%
other-relative	121	17.3%
not-in-family	119	17.0%
husband	116	16.6%
wife	116	16.6%
unmarried	101	14.4%

Most occurring characters

Value	Count	Frequency (%)
i	703	10.7%
n	582	8.9%
e	580	8.8%
-	486	7.4%
a	457	7.0%
r	444	6.8%
o	367	5.6%
l	367	5.6%
h	364	5.5%
t	361	5.5%
Other values (10)	1858	28.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6083	92.6%
Dash Punctuation	486	7.4%

Most frequent character per category

Value	Count	Frequency (%)
i	703	11.6%
n	582	9.6%
e	580	9.5%
a	457	7.5%
r	444	7.3%
o	367	6.0%
l	367	6.0%
h	364	6.0%
t	361	5.9%
d	344	5.7%
Other values (9)	1514	24.9%

Value	Count	Frequency (%)
-	486	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6083	92.6%
Common	486	7.4%

Most frequent character per script

Value	Count	Frequency (%)
i	703	11.6%
n	582	9.6%
e	580	9.5%
a	457	7.5%
r	444	7.3%
o	367	6.0%
l	367	6.0%
h	364	6.0%
t	361	5.9%
d	344	5.7%
Other values (9)	1514	24.9%

Value	Count	Frequency (%)
-	486	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6569	100.0%

Most frequent character per block

Value	Count	Frequency (%)
i	703	10.7%
n	582	8.9%
e	580	8.8%
-	486	7.4%
a	457	7.0%
r	444	6.8%
o	367	5.6%
l	367	5.6%
h	364	5.5%
t	361	5.5%
Other values (10)	1858	28.3%

capital-gains
Real number (ℝ_≥0)

ZEROS

Distinct	269
Distinct (%)	38.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	25777.57143
Minimum	0
Maximum	98800
Zeros	350
Zeros (%)	50.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	5000
Q3	52200
95-th percentile	71205
Maximum	98800
Range	98800
Interquartile range (IQR)	52200

Descriptive statistics

Standard deviation	28239.30078
Coefficient of variation (CV)	1.095498886
Kurtosis	-1.334480834
Mean	25777.57143
Median Absolute Deviation (MAD)	5000
Skewness	0.451444617
Sum	18044300
Variance	797458108.5
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	350	50.0%
68500	4	0.6%
46300	4	0.6%
29300	3	0.4%
52600	3	0.4%
45700	3	0.4%
63100	3	0.4%
51100	3	0.4%
75800	3	0.4%
63600	3	0.4%
Other values (259)	321	45.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	350	50.0%
10000	1	0.1%
11000	1	0.1%
12100	1	0.1%
12800	1	0.1%

Value	Count	Frequency (%)
98800	1	0.1%
91900	1	0.1%
90700	1	0.1%
88800	1	0.1%
88400	1	0.1%

capital-loss
Real number (ℝ)

ZEROS

Distinct	288
Distinct (%)	41.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	-27061
Minimum	-111100
Maximum	0
Zeros	326
Zeros (%)	46.6%
Memory size	5.6 KiB

Quantile statistics

Minimum	-111100
5-th percentile	-71405
Q1	-51825
median	-27450
Q3	0
95-th percentile	0
Maximum	0
Range	111100
Interquartile range (IQR)	51825

Descriptive statistics

Standard deviation	27874.24256
Coefficient of variation (CV)	-1.030052199
Kurtosis	-1.353650599
Mean	-27061
Median Absolute Deviation (MAD)	27450
Skewness	-0.3479678515
Sum	-18942700
Variance	776973398.1
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	326	46.6%
-50300	4	0.6%
-53700	4	0.6%
-31400	4	0.6%
-53800	4	0.6%
-31700	4	0.6%
-49200	3	0.4%
-67800	3	0.4%
-51000	3	0.4%
-55600	3	0.4%
Other values (278)	342	48.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-111100	1	0.1%
-91400	1	0.1%
-90200	1	0.1%
-89400	1	0.1%
-88300	1	0.1%

Value	Count	Frequency (%)
0	326	46.6%
-5700	1	0.1%
-6300	1	0.1%
-8500	1	0.1%
-10600	1	0.1%

policy_number
Real number (ℝ_≥0)

UNIQUE

Distinct	700
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	551898.9771
Minimum	100804
Maximum	998865
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	100804
5-th percentile	140921.75
Q1	337547.25
median	547773
Q3	775554.5
95-th percentile	964683.5
Maximum	998865
Range	898061
Interquartile range (IQR)	438007.25

Descriptive statistics

Standard deviation	260076.7729
Coefficient of variation (CV)	0.4712398169
Kurtosis	-1.147347575
Mean	551898.9771
Median Absolute Deviation (MAD)	215634
Skewness	0.0230165729
Sum	386329284
Variance	6.763992781 × 10¹⁰
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
296960	1	0.1%
620215	1	0.1%
810189	1	0.1%
139484	1	0.1%
140977	1	0.1%
326322	1	0.1%
489618	1	0.1%
743092	1	0.1%
674485	1	0.1%
419510	1	0.1%
Other values (690)	690	98.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
100804	1	0.1%
101421	1	0.1%
106873	1	0.1%
107181	1	0.1%
108270	1	0.1%

Value	Count	Frequency (%)
998865	1	0.1%
998192	1	0.1%
996850	1	0.1%
996253	1	0.1%
994538	1	0.1%

policy_bind_date
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	671
Distinct (%)	95.9%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

2006-01-01	3
1992-04-28	3
2007-05-06	2
2010-01-28	2
1997-07-14	2
Other values (666)	688

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	7000
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	644 ?
Unique (%)	92.0%

Sample

1st row	2013-11-11
2nd row	2005-12-09
3rd row	2001-11-29
4th row	2012-10-09
5th row	2004-01-02

Value	Count	Frequency (%)
2006-01-01	3	0.4%
1992-04-28	3	0.4%
2007-05-06	2	0.3%
2010-01-28	2	0.3%
1997-07-14	2	0.3%
2000-06-04	2	0.3%
1993-08-30	2	0.3%
2013-12-25	2	0.3%
1997-11-07	2	0.3%
1995-12-07	2	0.3%
Other values (661)	678	96.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
2006-01-01	3	0.4%
1992-04-28	3	0.4%
2007-05-06	2	0.3%
2010-01-28	2	0.3%
1997-07-14	2	0.3%
2000-06-04	2	0.3%
1993-08-30	2	0.3%
2013-12-25	2	0.3%
1997-11-07	2	0.3%
1995-12-07	2	0.3%
Other values (661)	678	96.9%

Most occurring characters

Value	Count	Frequency (%)
0	1606	22.9%
-	1400	20.0%
1	1125	16.1%
2	899	12.8%
9	803	11.5%
4	213	3.0%
3	210	3.0%
8	198	2.8%
7	189	2.7%
6	183	2.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5600	80.0%
Dash Punctuation	1400	20.0%

Most frequent character per category

Value	Count	Frequency (%)
0	1606	28.7%
1	1125	20.1%
2	899	16.1%
9	803	14.3%
4	213	3.8%
3	210	3.8%
8	198	3.5%
7	189	3.4%
6	183	3.3%
5	174	3.1%

Value	Count	Frequency (%)
-	1400	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	7000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	1606	22.9%
-	1400	20.0%
1	1125	16.1%
2	899	12.8%
9	803	11.5%
4	213	3.0%
3	210	3.0%
8	198	2.8%
7	189	2.7%
6	183	2.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	1606	22.9%
-	1400	20.0%
1	1125	16.1%
2	899	12.8%
9	803	11.5%
4	213	3.0%
3	210	3.0%
8	198	2.8%
7	189	2.7%
6	183	2.6%

policy_state
Categorical

Distinct	3
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

IL	241
OH	240
IN	219

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	1400
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	OH
2nd row	IN
3rd row	IN
4th row	IN
5th row	IL

Value	Count	Frequency (%)
IL	241	34.4%
OH	240	34.3%
IN	219	31.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
il	241	34.4%
oh	240	34.3%
in	219	31.3%

Most occurring characters

Value	Count	Frequency (%)
I	460	32.9%
L	241	17.2%
O	240	17.1%
H	240	17.1%
N	219	15.6%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1400	100.0%

Most frequent character per category

Value	Count	Frequency (%)
I	460	32.9%
L	241	17.2%
O	240	17.1%
H	240	17.1%
N	219	15.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1400	100.0%

Most frequent character per script

Value	Count	Frequency (%)
I	460	32.9%
L	241	17.2%
O	240	17.1%
H	240	17.1%
N	219	15.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1400	100.0%

Most frequent character per block

Value	Count	Frequency (%)
I	460	32.9%
L	241	17.2%
O	240	17.1%
H	240	17.1%
N	219	15.6%

policy_csl
Categorical

Distinct	3
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

250/500	241
100/300	237
500/1000	222

Length

Max length	8
Median length	7
Mean length	7.317142857
Min length	7

Characters and Unicode

Total characters	5122
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	250/500
2nd row	500/1000
3rd row	500/1000
4th row	500/1000
5th row	100/300

Value	Count	Frequency (%)
250/500	241	34.4%
100/300	237	33.9%
500/1000	222	31.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
250/500	241	34.4%
100/300	237	33.9%
500/1000	222	31.7%

Most occurring characters

Value	Count	Frequency (%)
0	2781	54.3%
5	704	13.7%
/	700	13.7%
1	459	9.0%
2	241	4.7%
3	237	4.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4422	86.3%
Other Punctuation	700	13.7%

Most frequent character per category

Value	Count	Frequency (%)
0	2781	62.9%
5	704	15.9%
1	459	10.4%
2	241	5.5%
3	237	5.4%

Value	Count	Frequency (%)
/	700	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	5122	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	2781	54.3%
5	704	13.7%
/	700	13.7%
1	459	9.0%
2	241	4.7%
3	237	4.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5122	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	2781	54.3%
5	704	13.7%
/	700	13.7%
1	459	9.0%
2	241	4.7%
3	237	4.6%

policy_deductable
Categorical

Distinct	3
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

500	241
1000	239
2000	220

Length

Max length	4
Median length	4
Mean length	3.655714286
Min length	3

Characters and Unicode

Total characters	2559
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1000
2nd row	2000
3rd row	500
4th row	500
5th row	2000

Value	Count	Frequency (%)
500	241	34.4%
1000	239	34.1%
2000	220	31.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
500	241	34.4%
1000	239	34.1%
2000	220	31.4%

Most occurring characters

Value	Count	Frequency (%)
0	1859	72.6%
5	241	9.4%
1	239	9.3%
2	220	8.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2559	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	1859	72.6%
5	241	9.4%
1	239	9.3%
2	220	8.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	2559	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	1859	72.6%
5	241	9.4%
1	239	9.3%
2	220	8.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2559	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	1859	72.6%
5	241	9.4%
1	239	9.3%
2	220	8.6%

incident_location
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct	700
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

2725 Britain Ridge	1
6574 4th Drive	1
1738 Solo Lane	1
3808 5th Ave	1
5769 Texas Lane	1
Other values (695)	695

Length

Max length	23
Median length	14
Mean length	14.79
Min length	11

Characters and Unicode

Total characters	10353
Distinct characters	49
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	700 ?
Unique (%)	100.0%

Sample

1st row	6303 1st Drive
2nd row	5585 Washington Drive
3rd row	1328 Texas Lane
4th row	6117 4th Ave
5th row	2272 Embaracadero Drive

Value	Count	Frequency (%)
2725 Britain Ridge	1	0.1%
6574 4th Drive	1	0.1%
1738 Solo Lane	1	0.1%
3808 5th Ave	1	0.1%
5769 Texas Lane	1	0.1%
5483 Francis Drive	1	0.1%
9070 Tree Ave	1	0.1%
3982 Washington Hwy	1	0.1%
7897 Lincoln St	1	0.1%
2048 3rd Ridge	1	0.1%
Other values (690)	690	98.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
drive	122	5.8%
st	121	5.8%
ave	120	5.7%
lane	118	5.6%
ridge	117	5.6%
hwy	102	4.9%
4th	41	2.0%
5th	35	1.7%
texas	34	1.6%
mlk	33	1.6%
Other values (695)	1257	59.9%

Most occurring characters

Value	Count	Frequency (%)
	1400	13.5%
e	885	8.5%
i	438	4.2%
a	430	4.2%
n	357	3.4%
r	348	3.4%
5	331	3.2%
t	328	3.2%
4	314	3.0%
3	310	3.0%
Other values (39)	5212	50.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4687	45.3%
Decimal Number	2931	28.3%
Space Separator	1400	13.5%
Uppercase Letter	1335	12.9%

Most frequent character per category

Value	Count	Frequency (%)
e	885	18.9%
i	438	9.3%
a	430	9.2%
n	357	7.6%
r	348	7.4%
t	328	7.0%
v	274	5.8%
d	224	4.8%
o	186	4.0%
h	149	3.2%
Other values (12)	1068	22.8%

Value	Count	Frequency (%)
L	178	13.3%
A	167	12.5%
S	164	12.3%
R	145	10.9%
D	122	9.1%
H	102	7.6%
T	61	4.6%
M	60	4.5%
F	59	4.4%
W	58	4.3%
Other values (6)	219	16.4%

Value	Count	Frequency (%)
5	331	11.3%
4	314	10.7%
3	310	10.6%
1	305	10.4%
2	302	10.3%
8	300	10.2%
7	296	10.1%
9	296	10.1%
6	272	9.3%
0	205	7.0%

Value	Count	Frequency (%)
	1400	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6022	58.2%
Common	4331	41.8%

Most frequent character per script

Value	Count	Frequency (%)
e	885	14.7%
i	438	7.3%
a	430	7.1%
n	357	5.9%
r	348	5.8%
t	328	5.4%
v	274	4.5%
d	224	3.7%
o	186	3.1%
L	178	3.0%
Other values (28)	2374	39.4%

Value	Count	Frequency (%)
	1400	32.3%
5	331	7.6%
4	314	7.3%
3	310	7.2%
1	305	7.0%
2	302	7.0%
8	300	6.9%
7	296	6.8%
9	296	6.8%
6	272	6.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10353	100.0%

Most frequent character per block

Value	Count	Frequency (%)
	1400	13.5%
e	885	8.5%
i	438	4.2%
a	430	4.2%
n	357	3.4%
r	348	3.4%
5	331	3.2%
t	328	3.2%
4	314	3.0%
3	310	3.0%
Other values (39)	5212	50.3%

incident_hour_of_the_day
Real number (ℝ_≥0)

ZEROS

Distinct	24
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	11.74714286
Minimum	0
Maximum	23
Zeros	40
Zeros (%)	5.7%
Memory size	5.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	6
median	12
Q3	17.25
95-th percentile	23
Maximum	23
Range	23
Interquartile range (IQR)	11.25

Descriptive statistics

Standard deviation	6.987444727
Coefficient of variation (CV)	0.5948207843
Kurtosis	-1.186013207
Mean	11.74714286
Median Absolute Deviation (MAD)	6
Skewness	-0.07359909252
Sum	8223
Variance	48.82438381
Monotocity	Not monotonic

Histogram with fixed size bins (bins=24)

Value	Count	Frequency (%)
17	41	5.9%
0	40	5.7%
23	36	5.1%
21	35	5.0%
3	34	4.9%
16	33	4.7%
12	33	4.7%
13	32	4.6%
9	29	4.1%
10	29	4.1%
Other values (14)	358	51.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	40	5.7%
1	21	3.0%
2	21	3.0%
3	34	4.9%
4	28	4.0%

Value	Count	Frequency (%)
23	36	5.1%
22	24	3.4%
21	35	5.0%
20	27	3.9%
19	27	3.9%

number_of_vehicles_involved
Categorical

Distinct	4
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

1	412
3	253
4	19
2	16

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	700
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	3
4th row	1
5th row	3

Value	Count	Frequency (%)
1	412	58.9%
3	253	36.1%
4	19	2.7%
2	16	2.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
1	412	58.9%
3	253	36.1%
4	19	2.7%
2	16	2.3%

Most occurring characters

Value	Count	Frequency (%)
1	412	58.9%
3	253	36.1%
4	19	2.7%
2	16	2.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	700	100.0%

Most frequent character per category

Value	Count	Frequency (%)
1	412	58.9%
3	253	36.1%
4	19	2.7%
2	16	2.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	700	100.0%

Most frequent character per script

Value	Count	Frequency (%)
1	412	58.9%
3	253	36.1%
4	19	2.7%
2	16	2.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	700	100.0%

Most frequent character per block

Value	Count	Frequency (%)
1	412	58.9%
3	253	36.1%
4	19	2.7%
2	16	2.3%

property_damage
Categorical

Distinct	3
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

?	255
NO	224
YES	221

Length

Max length	3
Median length	2
Mean length	1.951428571
Min length	1

Characters and Unicode

Total characters	1366
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	?
2nd row	NO
3rd row	NO
4th row	?
5th row	YES

Value	Count	Frequency (%)
?	255	36.4%
NO	224	32.0%
YES	221	31.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
	255	36.4%
no	224	32.0%
yes	221	31.6%

Most occurring characters

Value	Count	Frequency (%)
?	255	18.7%
N	224	16.4%
O	224	16.4%
Y	221	16.2%
E	221	16.2%
S	221	16.2%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1111	81.3%
Other Punctuation	255	18.7%

Most frequent character per category

Value	Count	Frequency (%)
N	224	20.2%
O	224	20.2%
Y	221	19.9%
E	221	19.9%
S	221	19.9%

Value	Count	Frequency (%)
?	255	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1111	81.3%
Common	255	18.7%

Most frequent character per script

Value	Count	Frequency (%)
N	224	20.2%
O	224	20.2%
Y	221	19.9%
E	221	19.9%
S	221	19.9%

Value	Count	Frequency (%)
?	255	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1366	100.0%

Most frequent character per block

Value	Count	Frequency (%)
?	255	18.7%
N	224	16.4%
O	224	16.4%
Y	221	16.2%
E	221	16.2%
S	221	16.2%

bodily_injuries
Categorical

Distinct	3
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

2	235
0	234
1	231

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	700
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	2

Value	Count	Frequency (%)
2	235	33.6%
0	234	33.4%
1	231	33.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
2	235	33.6%
0	234	33.4%
1	231	33.0%

Most occurring characters

Value	Count	Frequency (%)
2	235	33.6%
0	234	33.4%
1	231	33.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	700	100.0%

Most frequent character per category

Value	Count	Frequency (%)
2	235	33.6%
0	234	33.4%
1	231	33.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	700	100.0%

Most frequent character per script

Value	Count	Frequency (%)
2	235	33.6%
0	234	33.4%
1	231	33.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	700	100.0%

Most frequent character per block

Value	Count	Frequency (%)
2	235	33.6%
0	234	33.4%
1	231	33.0%

policy_annual_premium
Real number (ℝ_≥0)

Distinct	694
Distinct (%)	99.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1256.950357
Minimum	433.33
Maximum	2047.59
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	433.33
5-th percentile	840.943
Q1	1084.7025
median	1256.34
Q3	1423.89
95-th percentile	1653.4435
Maximum	2047.59
Range	1614.26
Interquartile range (IQR)	339.1875

Descriptive statistics

Standard deviation	249.6168023
Coefficient of variation (CV)	0.198589229
Kurtosis	0.1096787666
Mean	1256.950357
Median Absolute Deviation (MAD)	169.995
Skewness	-0.05557273268
Sum	879865.25
Variance	62308.54801
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1281.25	2	0.3%
1374.22	2	0.3%
1389.13	2	0.3%
1215.36	2	0.3%
1073.83	2	0.3%
1524.45	2	0.3%
1124.43	1	0.1%
1260.56	1	0.1%
1356.64	1	0.1%
1151.39	1	0.1%
Other values (684)	684	97.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
433.33	1	0.1%
484.67	1	0.1%
538.17	1	0.1%
566.11	1	0.1%
617.11	1	0.1%

Value	Count	Frequency (%)
2047.59	1	0.1%
1969.63	1	0.1%
1922.84	1	0.1%
1896.91	1	0.1%
1865.83	1	0.1%

umbrella_limit
Real number (ℝ_≥0)

ZEROS

Distinct	10
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1092857.143
Minimum	0
Maximum	10000000
Zeros	561
Zeros (%)	80.1%
Memory size	5.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	6000000
Maximum	10000000
Range	10000000
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2289793.328
Coefficient of variation (CV)	2.095235725
Kurtosis	1.747595947
Mean	1092857.143
Median Absolute Deviation (MAD)	0
Skewness	1.807292601
Sum	765000000
Variance	5.243153485 × 10¹²
Monotocity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	561	80.1%
6000000	37	5.3%
5000000	34	4.9%
4000000	25	3.6%
7000000	24	3.4%
3000000	8	1.1%
8000000	5	0.7%
9000000	3	0.4%
2000000	2	0.3%
10000000	1	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	561	80.1%
2000000	2	0.3%
3000000	8	1.1%
4000000	25	3.6%
5000000	34	4.9%

Value	Count	Frequency (%)
10000000	1	0.1%
9000000	3	0.4%
8000000	5	0.7%
7000000	24	3.4%
6000000	37	5.3%

insured_zip
Real number (ℝ_≥0)

Distinct	697
Distinct (%)	99.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	500211.26
Minimum	430104
Maximum	620869
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	430104
5-th percentile	433587
Q1	446952
median	465565
Q3	603417.5
95-th percentile	617740.75
Maximum	620869
Range	190765
Interquartile range (IQR)	156465.5

Descriptive statistics

Standard deviation	71731.67763
Coefficient of variation (CV)	0.1434027647
Kurtosis	-1.156487335
Mean	500211.26
Median Absolute Deviation (MAD)	21260
Skewness	0.8383224898
Sum	350147882
Variance	5145433575
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
477695	2	0.3%
456602	2	0.3%
431202	2	0.3%
453277	1	0.1%
474771	1	0.1%
472724	1	0.1%
471704	1	0.1%
452249	1	0.1%
453274	1	0.1%
615921	1	0.1%
Other values (687)	687	98.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
430104	1	0.1%
430141	1	0.1%
430232	1	0.1%
430380	1	0.1%
430567	1	0.1%

Value	Count	Frequency (%)
620869	1	0.1%
620819	1	0.1%
620757	1	0.1%
620737	1	0.1%
620507	1	0.1%

incident_date
Categorical

HIGH CARDINALITY

Distinct	60
Distinct (%)	8.6%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

2015-02-17	21
2015-02-02	19
2015-01-07	17
2015-02-04	17
2015-01-08	16
Other values (55)	610

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	7000
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2015-02-18
2nd row	2015-02-19
3rd row	2015-01-31
4th row	2015-02-05
5th row	2015-01-03

Value	Count	Frequency (%)
2015-02-17	21	3.0%
2015-02-02	19	2.7%
2015-01-07	17	2.4%
2015-02-04	17	2.4%
2015-01-08	16	2.3%
2015-01-19	16	2.3%
2015-02-22	15	2.1%
2015-01-24	15	2.1%
2015-01-03	15	2.1%
2015-01-21	15	2.1%
Other values (50)	534	76.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
2015-02-17	21	3.0%
2015-02-02	19	2.7%
2015-01-07	17	2.4%
2015-02-04	17	2.4%
2015-01-08	16	2.3%
2015-01-19	16	2.3%
2015-02-22	15	2.1%
2015-01-24	15	2.1%
2015-01-03	15	2.1%
2015-01-21	15	2.1%
Other values (50)	534	76.3%

Most occurring characters

Value	Count	Frequency (%)
0	1684	24.1%
-	1400	20.0%
1	1388	19.8%
2	1319	18.8%
5	759	10.8%
3	112	1.6%
7	78	1.1%
4	76	1.1%
8	72	1.0%
6	63	0.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5600	80.0%
Dash Punctuation	1400	20.0%

Most frequent character per category

Value	Count	Frequency (%)
0	1684	30.1%
1	1388	24.8%
2	1319	23.6%
5	759	13.6%
3	112	2.0%
7	78	1.4%
4	76	1.4%
8	72	1.3%
6	63	1.1%
9	49	0.9%

Value	Count	Frequency (%)
-	1400	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	7000	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	1684	24.1%
-	1400	20.0%
1	1388	19.8%
2	1319	18.8%
5	759	10.8%
3	112	1.6%
7	78	1.1%
4	76	1.1%
8	72	1.0%
6	63	0.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7000	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	1684	24.1%
-	1400	20.0%
1	1388	19.8%
2	1319	18.8%
5	759	10.8%
3	112	1.6%
7	78	1.1%
4	76	1.1%
8	72	1.0%
6	63	0.9%

incident_type
Categorical

Distinct	4
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Single Vehicle Collision	295
Multi-vehicle Collision	288
Vehicle Theft	60
Parked Car	57

Length

Max length	24
Median length	23
Mean length	21.50571429
Min length	10

Characters and Unicode

Total characters	15054
Distinct characters	25
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Parked Car
2nd row	Single Vehicle Collision
3rd row	Multi-vehicle Collision
4th row	Single Vehicle Collision
5th row	Multi-vehicle Collision

Value	Count	Frequency (%)
Single Vehicle Collision	295	42.1%
Multi-vehicle Collision	288	41.1%
Vehicle Theft	60	8.6%
Parked Car	57	8.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
collision	583	34.4%
vehicle	355	20.9%
single	295	17.4%
multi-vehicle	288	17.0%
theft	60	3.5%
parked	57	3.4%
car	57	3.4%

Most occurring characters

Value	Count	Frequency (%)
i	2392	15.9%
l	2392	15.9%
e	1698	11.3%
o	1166	7.7%
	995	6.6%
n	878	5.8%
h	703	4.7%
c	643	4.3%
C	640	4.3%
s	583	3.9%
Other values (15)	2964	19.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	12076	80.2%
Uppercase Letter	1695	11.3%
Space Separator	995	6.6%
Dash Punctuation	288	1.9%

Most frequent character per category

Value	Count	Frequency (%)
i	2392	19.8%
l	2392	19.8%
e	1698	14.1%
o	1166	9.7%
n	878	7.3%
h	703	5.8%
c	643	5.3%
s	583	4.8%
t	348	2.9%
g	295	2.4%
Other values (7)	978	8.1%

Value	Count	Frequency (%)
C	640	37.8%
V	355	20.9%
S	295	17.4%
M	288	17.0%
T	60	3.5%
P	57	3.4%

Value	Count	Frequency (%)
	995	100.0%

Value	Count	Frequency (%)
-	288	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	13771	91.5%
Common	1283	8.5%

Most frequent character per script

Value	Count	Frequency (%)
i	2392	17.4%
l	2392	17.4%
e	1698	12.3%
o	1166	8.5%
n	878	6.4%
h	703	5.1%
c	643	4.7%
C	640	4.6%
s	583	4.2%
V	355	2.6%
Other values (13)	2321	16.9%

Value	Count	Frequency (%)
	995	77.6%
-	288	22.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	15054	100.0%

Most frequent character per block

Value	Count	Frequency (%)
i	2392	15.9%
l	2392	15.9%
e	1698	11.3%
o	1166	7.7%
	995	6.6%
n	878	5.8%
h	703	4.7%
c	643	4.3%
C	640	4.3%
s	583	3.9%
Other values (15)	2964	19.7%

collision_type
Categorical

Distinct	4
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Rear Collision	204
Side Collision	197
Front Collision	182
?	117

Length

Max length	15
Median length	14
Mean length	12.08714286
Min length	1

Characters and Unicode

Total characters	8461
Distinct characters	16
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	?
2nd row	Rear Collision
3rd row	Front Collision
4th row	Front Collision
5th row	Front Collision

Value	Count	Frequency (%)
Rear Collision	204	29.1%
Side Collision	197	28.1%
Front Collision	182	26.0%
?	117	16.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
collision	583	45.4%
rear	204	15.9%
side	197	15.4%
front	182	14.2%
	117	9.1%

Most occurring characters

Value	Count	Frequency (%)
i	1363	16.1%
o	1348	15.9%
l	1166	13.8%
n	765	9.0%
	583	6.9%
C	583	6.9%
s	583	6.9%
e	401	4.7%
r	386	4.6%
R	204	2.4%
Other values (6)	1079	12.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6595	77.9%
Uppercase Letter	1166	13.8%
Space Separator	583	6.9%
Other Punctuation	117	1.4%

Most frequent character per category

Value	Count	Frequency (%)
i	1363	20.7%
o	1348	20.4%
l	1166	17.7%
n	765	11.6%
s	583	8.8%
e	401	6.1%
r	386	5.9%
a	204	3.1%
d	197	3.0%
t	182	2.8%

Value	Count	Frequency (%)
C	583	50.0%
R	204	17.5%
S	197	16.9%
F	182	15.6%

Value	Count	Frequency (%)
?	117	100.0%

Value	Count	Frequency (%)
	583	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7761	91.7%
Common	700	8.3%

Most frequent character per script

Value	Count	Frequency (%)
i	1363	17.6%
o	1348	17.4%
l	1166	15.0%
n	765	9.9%
C	583	7.5%
s	583	7.5%
e	401	5.2%
r	386	5.0%
R	204	2.6%
a	204	2.6%
Other values (4)	758	9.8%

Value	Count	Frequency (%)
	583	83.3%
?	117	16.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8461	100.0%

Most frequent character per block

Value	Count	Frequency (%)
i	1363	16.1%
o	1348	15.9%
l	1166	13.8%
n	765	9.0%
	583	6.9%
C	583	6.9%
s	583	6.9%
e	401	4.7%
r	386	4.6%
R	204	2.4%
Other values (6)	1079	12.8%

incident_severity
Categorical

Distinct	4
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Minor Damage	248
Total Loss	209
Major Damage	189
Trivial Damage	54

Length

Max length	14
Median length	12
Mean length	11.55714286
Min length	10

Characters and Unicode

Total characters	8090
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Trivial Damage
2nd row	Total Loss
3rd row	Major Damage
4th row	Major Damage
5th row	Total Loss

Value	Count	Frequency (%)
Minor Damage	248	35.4%
Total Loss	209	29.9%
Major Damage	189	27.0%
Trivial Damage	54	7.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
damage	491	35.1%
minor	248	17.7%
loss	209	14.9%
total	209	14.9%
major	189	13.5%
trivial	54	3.9%

Most occurring characters

Value	Count	Frequency (%)
a	1434	17.7%
o	855	10.6%
	700	8.7%
r	491	6.1%
D	491	6.1%
m	491	6.1%
g	491	6.1%
e	491	6.1%
M	437	5.4%
s	418	5.2%
Other values (8)	1791	22.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5990	74.0%
Uppercase Letter	1400	17.3%
Space Separator	700	8.7%

Most frequent character per category

Value	Count	Frequency (%)
a	1434	23.9%
o	855	14.3%
r	491	8.2%
m	491	8.2%
g	491	8.2%
e	491	8.2%
s	418	7.0%
i	356	5.9%
l	263	4.4%
n	248	4.1%
Other values (3)	452	7.5%

Value	Count	Frequency (%)
D	491	35.1%
M	437	31.2%
T	263	18.8%
L	209	14.9%

Value	Count	Frequency (%)
	700	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7390	91.3%
Common	700	8.7%

Most frequent character per script

Value	Count	Frequency (%)
a	1434	19.4%
o	855	11.6%
r	491	6.6%
D	491	6.6%
m	491	6.6%
g	491	6.6%
e	491	6.6%
M	437	5.9%
s	418	5.7%
i	356	4.8%
Other values (7)	1435	19.4%

Value	Count	Frequency (%)
	700	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8090	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	1434	17.7%
o	855	10.6%
	700	8.7%
r	491	6.1%
D	491	6.1%
m	491	6.1%
g	491	6.1%
e	491	6.1%
M	437	5.4%
s	418	5.2%
Other values (8)	1791	22.1%

authorities_contacted
Categorical

Distinct	5
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Police	203
Fire	164
Ambulance	138
Other	136
None	59

Length

Max length	9
Median length	5
Mean length	5.76
Min length	4

Characters and Unicode

Total characters	4032
Distinct characters	18
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Police
2nd row	Fire
3rd row	Other
4th row	Other
5th row	Police

Value	Count	Frequency (%)
Police	203	29.0%
Fire	164	23.4%
Ambulance	138	19.7%
Other	136	19.4%
None	59	8.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
police	203	29.0%
fire	164	23.4%
ambulance	138	19.7%
other	136	19.4%
none	59	8.4%

Most occurring characters

Value	Count	Frequency (%)
e	700	17.4%
i	367	9.1%
l	341	8.5%
c	341	8.5%
r	300	7.4%
o	262	6.5%
P	203	5.0%
n	197	4.9%
F	164	4.1%
A	138	3.4%
Other values (8)	1019	25.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3332	82.6%
Uppercase Letter	700	17.4%

Most frequent character per category

Value	Count	Frequency (%)
e	700	21.0%
i	367	11.0%
l	341	10.2%
c	341	10.2%
r	300	9.0%
o	262	7.9%
n	197	5.9%
m	138	4.1%
b	138	4.1%
u	138	4.1%
Other values (3)	410	12.3%

Value	Count	Frequency (%)
P	203	29.0%
F	164	23.4%
A	138	19.7%
O	136	19.4%
N	59	8.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4032	100.0%

Most frequent character per script

Value	Count	Frequency (%)
e	700	17.4%
i	367	9.1%
l	341	8.5%
c	341	8.5%
r	300	7.4%
o	262	6.5%
P	203	5.0%
n	197	4.9%
F	164	4.1%
A	138	3.4%
Other values (8)	1019	25.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4032	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	700	17.4%
i	367	9.1%
l	341	8.5%
c	341	8.5%
r	300	7.4%
o	262	6.5%
P	203	5.0%
n	197	4.9%
F	164	4.1%
A	138	3.4%
Other values (8)	1019	25.3%

incident_state
Categorical

Distinct	7
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

NY	197
SC	166
WV	149
VA	80
NC	74
Other values (2)	34

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	1400
Distinct characters	10
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NC
2nd row	NY
3rd row	WV
4th row	WV
5th row	WV

Value	Count	Frequency (%)
NY	197	28.1%
SC	166	23.7%
WV	149	21.3%
VA	80	11.4%
NC	74	10.6%
OH	17	2.4%
PA	17	2.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
ny	197	28.1%
sc	166	23.7%
wv	149	21.3%
va	80	11.4%
nc	74	10.6%
pa	17	2.4%
oh	17	2.4%

Most occurring characters

Value	Count	Frequency (%)
N	271	19.4%
C	240	17.1%
V	229	16.4%
Y	197	14.1%
S	166	11.9%
W	149	10.6%
A	97	6.9%
O	17	1.2%
H	17	1.2%
P	17	1.2%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1400	100.0%

Most frequent character per category

Value	Count	Frequency (%)
N	271	19.4%
C	240	17.1%
V	229	16.4%
Y	197	14.1%
S	166	11.9%
W	149	10.6%
A	97	6.9%
O	17	1.2%
H	17	1.2%
P	17	1.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1400	100.0%

Most frequent character per script

Value	Count	Frequency (%)
N	271	19.4%
C	240	17.1%
V	229	16.4%
Y	197	14.1%
S	166	11.9%
W	149	10.6%
A	97	6.9%
O	17	1.2%
H	17	1.2%
P	17	1.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1400	100.0%

Most frequent character per block

Value	Count	Frequency (%)
N	271	19.4%
C	240	17.1%
V	229	16.4%
Y	197	14.1%
S	166	11.9%
W	149	10.6%
A	97	6.9%
O	17	1.2%
H	17	1.2%
P	17	1.2%

incident_city
Categorical

Distinct	7
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Springfield	118
Northbend	106
Columbus	102
Hillsdale	101
Arlington	95
Other values (2)	178

Length

Max length	11
Median length	9
Mean length	9.314285714
Min length	8

Characters and Unicode

Total characters	6520
Distinct characters	26
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Arlington
2nd row	Columbus
3rd row	Riverwood
4th row	Columbus
5th row	Springfield

Value	Count	Frequency (%)
Springfield	118	16.9%
Northbend	106	15.1%
Columbus	102	14.6%
Hillsdale	101	14.4%
Arlington	95	13.6%
Riverwood	92	13.1%
Northbrook	86	12.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
springfield	118	16.9%
northbend	106	15.1%
columbus	102	14.6%
hillsdale	101	14.4%
arlington	95	13.6%
riverwood	92	13.1%
northbrook	86	12.3%

Most occurring characters

Value	Count	Frequency (%)
o	745	11.4%
l	618	9.5%
r	583	8.9%
i	524	8.0%
e	417	6.4%
d	417	6.4%
n	414	6.3%
b	294	4.5%
t	287	4.4%
g	213	3.3%
Other values (16)	2008	30.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5820	89.3%
Uppercase Letter	700	10.7%

Most frequent character per category

Value	Count	Frequency (%)
o	745	12.8%
l	618	10.6%
r	583	10.0%
i	524	9.0%
e	417	7.2%
d	417	7.2%
n	414	7.1%
b	294	5.1%
t	287	4.9%
g	213	3.7%
Other values (10)	1308	22.5%

Value	Count	Frequency (%)
N	192	27.4%
S	118	16.9%
C	102	14.6%
H	101	14.4%
A	95	13.6%
R	92	13.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6520	100.0%

Most frequent character per script

Value	Count	Frequency (%)
o	745	11.4%
l	618	9.5%
r	583	8.9%
i	524	8.0%
e	417	6.4%
d	417	6.4%
n	414	6.3%
b	294	4.5%
t	287	4.4%
g	213	3.3%
Other values (16)	2008	30.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6520	100.0%

Most frequent character per block

Value	Count	Frequency (%)
o	745	11.4%
l	618	9.5%
r	583	8.9%
i	524	8.0%
e	417	6.4%
d	417	6.4%
n	414	6.3%
b	294	4.5%
t	287	4.4%
g	213	3.3%
Other values (16)	2008	30.8%

witnesses
Categorical

Distinct	4
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

0	191
1	179
3	171
2	159

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	700
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	3
4th row	0
5th row	2

Value	Count	Frequency (%)
0	191	27.3%
1	179	25.6%
3	171	24.4%
2	159	22.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	191	27.3%
1	179	25.6%
3	171	24.4%
2	159	22.7%

Most occurring characters

Value	Count	Frequency (%)
0	191	27.3%
1	179	25.6%
3	171	24.4%
2	159	22.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	700	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	191	27.3%
1	179	25.6%
3	171	24.4%
2	159	22.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	700	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	191	27.3%
1	179	25.6%
3	171	24.4%
2	159	22.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	700	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	191	27.3%
1	179	25.6%
3	171	24.4%
2	159	22.7%

police_report_available
Categorical

Distinct	3
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

NO	250
YES	226
?	224

Length

Max length	3
Median length	2
Mean length	2.002857143
Min length	1

Characters and Unicode

Total characters	1402
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	YES
2nd row	NO
3rd row	?
4th row	?
5th row	YES

Value	Count	Frequency (%)
NO	250	35.7%
YES	226	32.3%
?	224	32.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
no	250	35.7%
yes	226	32.3%
	224	32.0%

Most occurring characters

Value	Count	Frequency (%)
N	250	17.8%
O	250	17.8%
Y	226	16.1%
E	226	16.1%
S	226	16.1%
?	224	16.0%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1178	84.0%
Other Punctuation	224	16.0%

Most frequent character per category

Value	Count	Frequency (%)
N	250	21.2%
O	250	21.2%
Y	226	19.2%
E	226	19.2%
S	226	19.2%

Value	Count	Frequency (%)
?	224	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1178	84.0%
Common	224	16.0%

Most frequent character per script

Value	Count	Frequency (%)
N	250	21.2%
O	250	21.2%
Y	226	19.2%
E	226	19.2%
S	226	19.2%

Value	Count	Frequency (%)
?	224	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1402	100.0%

Most frequent character per block

Value	Count	Frequency (%)
N	250	17.8%
O	250	17.8%
Y	226	16.1%
E	226	16.1%
S	226	16.1%
?	224	16.0%

auto_make
Categorical

HIGH CORRELATION

Distinct	14
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Dodge	55
Saab	55
BMW	54
Volkswagen	54
Nissan	53
Other values (9)	429

Length

Max length	10
Median length	6
Mean length	5.731428571
Min length	3

Characters and Unicode

Total characters	4012
Distinct characters	33
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mercedes
2nd row	Dodge
3rd row	Volkswagen
4th row	Toyota
5th row	Volkswagen

Value	Count	Frequency (%)
Dodge	55	7.9%
Saab	55	7.9%
BMW	54	7.7%
Volkswagen	54	7.7%
Nissan	53	7.6%
Accura	53	7.6%
Jeep	53	7.6%
Chevrolet	51	7.3%
Suburu	50	7.1%
Mercedes	48	6.9%
Other values (4)	174	24.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
saab	55	7.9%
dodge	55	7.9%
volkswagen	54	7.7%
bmw	54	7.7%
nissan	53	7.6%
jeep	53	7.6%
accura	53	7.6%
chevrolet	51	7.3%
suburu	50	7.1%
mercedes	48	6.9%
Other values (4)	174	24.9%

Most occurring characters

Value	Count	Frequency (%)
e	461	11.5%
a	353	8.8%
o	335	8.3%
r	249	6.2%
u	247	6.2%
d	232	5.8%
s	208	5.2%
c	154	3.8%
n	145	3.6%
g	109	2.7%
Other values (23)	1519	37.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3204	79.9%
Uppercase Letter	808	20.1%

Most frequent character per category

Value	Count	Frequency (%)
e	461	14.4%
a	353	11.0%
o	335	10.5%
r	249	7.8%
u	247	7.7%
d	232	7.2%
s	208	6.5%
c	154	4.8%
n	145	4.5%
g	109	3.4%
Other values (10)	711	22.2%

Value	Count	Frequency (%)
S	105	13.0%
M	102	12.6%
A	97	12.0%
D	55	6.8%
V	54	6.7%
B	54	6.7%
W	54	6.7%
J	53	6.6%
N	53	6.6%
C	51	6.3%
Other values (3)	130	16.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4012	100.0%

Most frequent character per script

Value	Count	Frequency (%)
e	461	11.5%
a	353	8.8%
o	335	8.3%
r	249	6.2%
u	247	6.2%
d	232	5.8%
s	208	5.2%
c	154	3.8%
n	145	3.6%
g	109	2.7%
Other values (23)	1519	37.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4012	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	461	11.5%
a	353	8.8%
o	335	8.3%
r	249	6.2%
u	247	6.2%
d	232	5.8%
s	208	5.2%
c	154	3.8%
n	145	3.6%
g	109	2.7%
Other values (23)	1519	37.9%

auto_model
Categorical

HIGH CORRELATION

Distinct	39
Distinct (%)	5.6%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Wrangler	33
MDX	32
Jetta	30
RAM	29
Neon	26
Other values (34)	550

Length

Max length	14
Median length	5
Mean length	5.185714286
Min length	2

Characters and Unicode

Total characters	3630
Distinct characters	52
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	E400
2nd row	Neon
3rd row	Passat
4th row	Corolla
5th row	Jetta

Value	Count	Frequency (%)
Wrangler	33	4.7%
MDX	32	4.6%
Jetta	30	4.3%
RAM	29	4.1%
Neon	26	3.7%
A3	25	3.6%
Passat	24	3.4%
E400	22	3.1%
Camry	21	3.0%
Pathfinder	21	3.0%
Other values (29)	437	62.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
wrangler	33	4.5%
mdx	32	4.4%
jetta	30	4.1%
ram	29	4.0%
neon	26	3.5%
a3	25	3.4%
passat	24	3.3%
e400	22	3.0%
pathfinder	21	2.9%
camry	21	2.9%
Other values (31)	470	64.1%

Most occurring characters

Value	Count	Frequency (%)
a	343	9.4%
e	306	8.4%
r	280	7.7%
o	162	4.5%
i	160	4.4%
t	139	3.8%
n	129	3.6%
M	125	3.4%
l	119	3.3%
s	112	3.1%
Other values (42)	1755	48.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2327	64.1%
Uppercase Letter	870	24.0%
Decimal Number	400	11.0%
Space Separator	33	0.9%

Most frequent character per category

Value	Count	Frequency (%)
a	343	14.7%
e	306	13.1%
r	280	12.0%
o	162	7.0%
i	160	6.9%
t	139	6.0%
n	129	5.5%
l	119	5.1%
s	112	4.8%
d	78	3.4%
Other values (13)	499	21.4%

Value	Count	Frequency (%)
M	125	14.4%
C	95	10.9%
A	79	9.1%
X	72	8.3%
R	58	6.7%
F	52	6.0%
P	45	5.2%
L	44	5.1%
S	42	4.8%
E	37	4.3%
Other values (10)	221	25.4%

Value	Count	Frequency (%)
5	98	24.5%
0	97	24.2%
3	81	20.2%
9	55	13.8%
4	22	5.5%
2	20	5.0%
1	16	4.0%
6	11	2.8%

Value	Count	Frequency (%)
	33	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3197	88.1%
Common	433	11.9%

Most frequent character per script

Value	Count	Frequency (%)
a	343	10.7%
e	306	9.6%
r	280	8.8%
o	162	5.1%
i	160	5.0%
t	139	4.3%
n	129	4.0%
M	125	3.9%
l	119	3.7%
s	112	3.5%
Other values (33)	1322	41.4%

Value	Count	Frequency (%)
5	98	22.6%
0	97	22.4%
3	81	18.7%
9	55	12.7%
	33	7.6%
4	22	5.1%
2	20	4.6%
1	16	3.7%
6	11	2.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3630	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	343	9.4%
e	306	8.4%
r	280	7.7%
o	162	4.5%
i	160	4.4%
t	139	3.8%
n	129	3.6%
M	125	3.4%
l	119	3.3%
s	112	3.1%
Other values (42)	1755	48.3%

auto_year
Real number (ℝ_≥0)

Distinct	21
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	2004.984286
Minimum	1995
Maximum	2015
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	1995
5-th percentile	1995
Q1	2000
median	2005
Q3	2010
95-th percentile	2014
Maximum	2015
Range	20
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	6.013198067
Coefficient of variation (CV)	0.002999124786
Kurtosis	-1.179731951
Mean	2004.984286
Median Absolute Deviation (MAD)	5
Skewness	-0.07404549759
Sum	1403489
Variance	36.15855099
Monotocity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
1995	47	6.7%
2011	43	6.1%
2007	41	5.9%
2002	38	5.4%
2009	38	5.4%
2005	37	5.3%
1999	37	5.3%
2008	35	5.0%
1997	35	5.0%
2012	35	5.0%
Other values (11)	314	44.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1995	47	6.7%
1996	24	3.4%
1997	35	5.0%
1998	22	3.1%
1999	37	5.3%

Value	Count	Frequency (%)
2015	28	4.0%
2014	27	3.9%
2013	31	4.4%
2012	35	5.0%
2011	43	6.1%

_c39
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	700
Missing (%)	100.0%
Memory size	5.6 KiB

total_claim_amount
Real number (ℝ_≥0)

Distinct	572
Distinct (%)	81.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	71900.93321
Minimum	133.33
Maximum	153226.67
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	133.33
5-th percentile	6265.3365
Q1	58933.33
median	77733.33
Q3	95503.3325
95-th percentile	118230.6635
Maximum	153226.67
Range	153093.34
Interquartile range (IQR)	36570.0025

Descriptive statistics

Standard deviation	34915.97492
Coefficient of variation (CV)	0.4856122635
Kurtosis	-0.330594352
Mean	71900.93321
Median Absolute Deviation (MAD)	18506.665
Skewness	-0.6208198363
Sum	50330653.25
Variance	1219125305
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
93866.67	4	0.6%
100533.33	4	0.6%
73333.33	3	0.4%
8533.33	3	0.4%
106400	3	0.4%
79200	3	0.4%
6160	3	0.4%
80800	3	0.4%
73600	3	0.4%
58933.33	3	0.4%
Other values (562)	668	95.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
133.33	1	0.1%
2560	1	0.1%
2880	1	0.1%
3200	1	0.1%
3520	2	0.3%

Value	Count	Frequency (%)
153226.67	1	0.1%
149760	1	0.1%
144640	1	0.1%
144040	1	0.1%
143866.67	1	0.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Customer_ID	months_as_customer	age	insured_sex	insured_education_level	insured_occupation	insured_hobbies	insured_relationship	capital-gains	capital-loss	policy_number	policy_bind_date	policy_state	policy_csl	policy_deductable	incident_location	incident_hour_of_the_day	number_of_vehicles_involved	property_damage	bodily_injuries	policy_annual_premium	umbrella_limit	insured_zip	incident_date	incident_type	collision_type	incident_severity	authorities_contacted	incident_state	incident_city	witnesses	police_report_available	auto_make	auto_model	auto_year	_c39	total_claim_amount
0	Customer_541	239	41	FEMALE	JD	farming-fishing	paintball	other-relative	51400	-6300	743092	2013-11-11	OH	250/500	1000	6303 1st Drive	22	1	?	0	1325.44	7000000	474898	2015-02-18	Parked Car	?	Trivial Damage	Police	NC	Arlington	2	YES	Mercedes	E400	2013	NaN	14386.67
1	Customer_440	108	31	MALE	Masters	protective-serv	yachting	not-in-family	0	0	492224	2005-12-09	IN	500/1000	2000	5585 Washington Drive	14	1	NO	0	1175.70	0	608767	2015-02-19	Single Vehicle Collision	Rear Collision	Total Loss	Fire	NY	Columbus	2	NO	Dodge	Neon	2006	NaN	76440.00
2	Customer_482	116	30	MALE	JD	handlers-cleaners	golf	not-in-family	0	-35500	996253	2001-11-29	IN	500/1000	500	1328 Texas Lane	8	3	NO	0	951.46	0	467227	2015-01-31	Multi-vehicle Collision	Front Collision	Major Damage	Other	WV	Riverwood	3	?	Volkswagen	Passat	2004	NaN	79560.00
3	Customer_422	8	21	MALE	High School	handlers-cleaners	hiking	husband	0	0	355085	2012-10-09	IN	500/1000	500	6117 4th Ave	21	1	?	0	1021.90	0	464237	2015-02-05	Single Vehicle Collision	Front Collision	Major Damage	Other	WV	Columbus	0	?	Toyota	Corolla	2012	NaN	121680.00
4	Customer_778	161	38	MALE	PhD	priv-house-serv	exercise	not-in-family	60200	0	192524	2004-01-02	IL	100/300	2000	2272 Embaracadero Drive	0	3	YES	2	1133.85	0	439870	2015-01-03	Multi-vehicle Collision	Front Collision	Total Loss	Police	WV	Springfield	2	YES	Volkswagen	Jetta	2003	NaN	80640.00
5	Customer_949	407	55	FEMALE	PhD	tech-support	bungie-jumping	wife	0	-57700	193213	1996-03-11	OH	100/300	1000	1806 Weaver Ridge	0	3	?	2	1250.08	5000000	474598	2015-02-08	Multi-vehicle Collision	Side Collision	Total Loss	Police	WV	Arlington	3	YES	Ford	Escape	2010	NaN	90880.00
6	Customer_334	96	30	MALE	College	prof-specialty	hiking	wife	38900	-48700	406567	2001-09-25	OH	100/300	500	9417 Tree Hwy	22	1	?	0	1399.27	6000000	448913	2015-02-24	Single Vehicle Collision	Side Collision	Total Loss	Fire	NC	Arlington	0	YES	Ford	Escape	2004	NaN	71253.33
7	Customer_576	282	46	MALE	MD	other-service	dancing	wife	51100	-75100	502634	1991-08-17	OH	100/300	2000	7954 Tree Ridge	2	1	?	2	1558.86	0	450800	2015-02-17	Single Vehicle Collision	Front Collision	Minor Damage	Police	NY	Springfield	2	NO	BMW	M5	2012	NaN	92533.33
8	Customer_934	146	31	FEMALE	College	armed-forces	camping	own-child	0	0	149839	1990-09-21	OH	100/300	1000	1110 4th Drive	0	3	NO	1	1457.65	5000000	606219	2015-02-03	Multi-vehicle Collision	Rear Collision	Major Damage	Ambulance	VA	Riverwood	3	?	Toyota	Highlander	2010	NaN	69840.00
9	Customer_567	371	54	MALE	High School	craft-repair	movies	wife	34700	-81000	403776	2012-04-27	IN	100/300	2000	6971 Best Ridge	18	3	?	1	1317.97	0	469853	2015-01-18	Multi-vehicle Collision	Front Collision	Major Damage	Ambulance	SC	Columbus	2	?	Ford	Fusion	2010	NaN	43040.00

Last rows

	Customer_ID	months_as_customer	age	insured_sex	insured_education_level	insured_occupation	insured_hobbies	insured_relationship	capital-gains	capital-loss	policy_number	policy_bind_date	policy_state	policy_csl	policy_deductable	incident_location	incident_hour_of_the_day	number_of_vehicles_involved	property_damage	bodily_injuries	policy_annual_premium	umbrella_limit	insured_zip	incident_date	incident_type	collision_type	incident_severity	authorities_contacted	incident_state	incident_city	witnesses	police_report_available	auto_make	auto_model	auto_year	_c39	total_claim_amount
690	Customer_121	206	36	FEMALE	MD	other-service	video-games	other-relative	0	-53700	253791	2009-07-23	IL	500/1000	500	2100 MLK St	11	1	NO	2	1625.45	4000000	607452	2015-01-23	Single Vehicle Collision	Front Collision	Major Damage	Ambulance	NY	Northbrook	1	NO	Ford	Fusion	2008	NaN	102080.00
691	Customer_614	131	33	MALE	MD	sales	yachting	wife	0	-65200	432740	1990-10-09	IL	100/300	2000	3246 Britain Ridge	3	1	?	0	1081.17	0	445120	2015-01-28	Parked Car	?	Minor Damage	Police	NY	Northbend	1	NO	Toyota	Camry	2010	NaN	6533.33
692	Customer_20	460	62	MALE	JD	other-service	bungie-jumping	own-child	0	0	183430	2002-06-25	IN	250/500	1000	5380 Pine St	20	3	NO	1	1187.96	4000000	618845	2015-01-01	Multi-vehicle Collision	Rear Collision	Minor Damage	Police	NY	Columbus	0	?	Suburu	Impreza	2011	NaN	62880.00
693	Customer_700	85	31	FEMALE	MD	tech-support	paintball	husband	0	0	873384	2004-03-10	IL	250/500	2000	7733 Britain Lane	1	2	NO	2	1234.69	9000000	613471	2015-02-06	Multi-vehicle Collision	Front Collision	Major Damage	Other	WV	Arlington	1	?	BMW	M5	2003	NaN	99200.00
694	Customer_71	222	41	FEMALE	MD	armed-forces	cross-fit	not-in-family	37800	-50300	260845	1998-11-11	OH	100/300	2000	6751 Pine Ridge	7	1	NO	0	1055.53	0	441992	2015-02-08	Single Vehicle Collision	Front Collision	Total Loss	Other	WV	Northbrook	2	NO	Honda	Civic	1995	NaN	81720.00
695	Customer_106	464	61	FEMALE	Associate	prof-specialty	basketball	husband	0	-56400	632627	1990-10-07	OH	500/1000	1000	4793 4th Ridge	6	3	?	0	1125.37	0	604450	2015-01-13	Multi-vehicle Collision	Rear Collision	Major Damage	Police	VA	Northbend	2	YES	Saab	95	2000	NaN	106400.00
696	Customer_270	369	55	MALE	College	handlers-cleaners	camping	husband	55400	0	577810	2013-04-15	OH	250/500	2000	9373 Pine Hwy	6	3	?	2	1589.54	0	444734	2015-01-27	Multi-vehicle Collision	Rear Collision	Minor Damage	Police	VA	Arlington	0	YES	Toyota	Highlander	2003	NaN	113733.33
697	Customer_860	230	42	FEMALE	MD	adm-clerical	golf	own-child	0	-45300	175960	2004-11-16	IN	100/300	1000	1589 Best Ave	13	3	NO	1	1023.11	0	476130	2015-02-06	Multi-vehicle Collision	Rear Collision	Minor Damage	Other	NY	Northbend	2	YES	Accura	MDX	1999	NaN	78466.67
698	Customer_435	102	28	MALE	MD	machine-op-inspct	reading	wife	55200	0	810189	1999-08-29	OH	250/500	500	8021 Flute Ave	6	1	NO	1	1075.41	0	445648	2015-02-15	Single Vehicle Collision	Side Collision	Total Loss	Police	PA	Northbend	0	NO	Dodge	Neon	1996	NaN	97866.67
699	Customer_102	279	41	FEMALE	JD	prof-specialty	bungie-jumping	husband	37300	-31700	389238	2001-06-06	IL	250/500	500	2199 Texas Drive	16	3	?	2	1497.35	0	460742	2015-01-29	Multi-vehicle Collision	Front Collision	Minor Damage	Fire	NC	Northbrook	3	NO	Ford	Fusion	2013	NaN	38400.00

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters